# Description
Fixes: #12726 and #13185
Previously converting columns that contained null caused polars to force
a dtype of object even when using a schema.
Now:
1. When using a schema, the type the schema defines for the column will
always be used.
2. When a schema is not used, the previous type is used when a value is
null.
# User-Facing Changes
- The type defined by the schema we be respected when passing in a null
value `[a]; [null] | polars into-df -s {a: str}` will create a df with
an str dtype column with one null value versus a column of type object.
- *BREAKING CHANGE* If you define a schema, all columns must be in the
schema.
# Description
This PR:
- Removes the lazy_command, expr_command macros and migrates the
commands that were utilizing them.
- Removes the custom logic in DataFrameValues::is_equals to use the
polars DataFrame version of PartialEq
- Adds examples to commands that previously did not have examples or had
inadequate ones.
NOTE: A lot of examples now have a `polars sort` at the end. This is
needed due to the comparison in the result. The new polars version of
equals cares about the ordering. I removed the custom equals logic as it
causes comparisons to lock up when comparing dataframes that contain a
row that contains a list. I discovered this issue when adding examples
to `polars implode`
